The breakthrough in the search for a coronavirus vaccine highlights the speed with which the pharmaceutical industry can mobilise scientific ingenuity in the service of humankind’s core goals. Yet, industry leaders know that such speed is the exception to the norm. Here, John Young, APAC director at automation parts supplier EU Automation, looks at four areas where greater automation could have a significant impact in helping speed the process of bringing a new drug to market in the years ahead.
The Asia-Pacific pharmaceutical sector is set to grow at a compound annual growth rate (CAGR) of 7.1 per cent in the period to 2027. Manufacturers wanting to take advantage of these opportunities should stay informed about the latest trends in automation technology. Unfortunately, many key decision-makers fear their companies will struggle to keep pace with technological innovation in this highly regulated sector. Here are four key areas where greater levels of automation could have a positive impact on the industry in the coming years:
In drug discovery, the chances of discovering a compound that produces the desired impact on the target is very low, so scientists typically check hundreds of thousands of potential compounds. This screening process, due to the high volume, is known as high throughput screening (HTS).
Automation plays a key role in HTS. Robotics and other forms of automation technology are a key part of any HTS system. Robots will transport assay plates from station to station and specialised automation analysis will often be used to run experiments on the wells. For example, measuring reflectivity to show evidence of protein binding.
Manufacturers are considering greater levels of automation to speed up the process and free up skilled workers for other tasks. When 100,000 or more compounds are screened in a single day, the process is sometimes known as ultra-high throughput screening. Naturally, screening on this scale involves significant automation, such as multiple robotic arms operating as colony pickers.
An effective way of automating the screening and experimenting referred to above is through investing in robotic liquid handling devices. The simplest version dispenses a fixed volume of liquid from a motorised pipette or syringe.
Adding greater levels of automation, such as a Cartesian coordinate robot, allows for the position of the pipette to be altered. The latest systems are highly precise, even when dispensing liquids on the nanolitre scale. Robotic liquid handling has been used to manage precise quantities of coronavirus, for instance, saving time by speeding up repetitive work, reducing the risk of error and lessening the exposure of human beings to the virus.
Robotic liquid handling systems are becoming increasingly versatile. An automated workstation can combine multiple operations into a single footprint, helping save floorspace in the laboratory. They can also be customised with different add-on modules, from centrifuges to colony pickers.
Quality Control (QC) is another key area where pharmaceuticals manufacturing may be missing out by not investing early in automated technologies. QC is especially important in any industry, but in pharmaceutical manufacturing, the stakes could not be higher. By reducing the need for human intervention, automation reduces human error.
Repetitive tasks can be automated to free up time and resources. These include, for example, colony counts, incubation transfers and data entry. Concerning the latter, many QC labs at the forefront of technological change are increasingly paperless. Data transcription is being automated and advanced data analytics software is capturing realtime insights.
Automated laboratories might also use predictive maintenance technologies to help schedule infrequent tasks like planned equipment maintenance. By pairing predictive maintenance technology with a reliable equipment supplier like EU Automation, laboratories can reduce the potential for costly downtime.
Automation will not replace the need for qualified QC managers and technicians, but it will enable them to perform their jobs more effectively. Many of the technologies that could achieve this are already available, but QC leaders often struggle to make a convincing business case to secure investment in digitising and automation their laboratories.
The idea that medicine should be tailored to the specific needs of the patient is an idea as old as the Hippocratic Oath, but the scientific breakthroughs of recent years have led to excited talk of ‘personalised medicine’. Also known as precision medicine or stratified medicine, the concept promises to revolutionise the world of healthcare delivery.
The successful mapping of the human genome has played a key role in opening the possibilities of personalised medicine. Specifically, sequencing an individual’s DNA or RNA can reveal genetic mutations that increase an individual’s risk level and susceptibility to certain diseases.
In terms of drug delivery, analysing an individual’s DNA, RNA or other biomarkers can help identify which drugs will be most effective for them or identify if they are more at risk of developing certain side effects, an area called pharmacogenomics. In short, it means abandoning the traditional trial and error strategy used by most doctors and replacing it with a method that is tailored to a unique individual.
This approach may play an important role in securing approval for drugs, helping reduce the excessive costs of bringing a drug to the market. This is because it will allow scientists to identify who will benefit most from a clinical trial. Furthermore, the threshold of efficacy for passing through the clinical trial stage could be lowered, because personalised genomes can be used to single out individuals who might benefit most from the drug.
Automation will be essential in fulfilling the revolutionary promise of personalised medicine. Many of the technologies associated with personalised medicine will rely on the generation of vast quantities of data and an appropriate digital infrastructure. As things currently stand, the capacity to gather the data is ahead of our capacity to analyse it.
Processing and analysing the data will require artificial intelligence and deep learning algorithms. However, the scale and pace of data generation will continue to grow as digitally enabled devices, including wearable devices and implantable sensors, become more common and accessible.
Automation plays a role in many stages of drug discovery and development. Although the speedy development of a coronavirus vaccine will remain the exception to the norm, strategic investments in automation will allow the pharmaceutical industry to speed up the process of bringing drugs to market in the coming years.